Distributed Systems

Without established design patterns to guide them, developers have had to build distributed systems from scratch, and most of these systems are very unique indeed. Today, the increasing use of containers has paved the way for core distributed system patterns and reusable containerized components. This practical guide presents a collection of repeatable, generic patterns to help make the development of reliable distributed systems far more approachable and efficient.

Author Brendan Burns—Director of Engineering at Microsoft Azure—demonstrates how you can adapt existing software design patterns for designing and building reliable distributed applications. Systems engineers and application developers will learn how these long-established patterns provide a common language and framework for dramatically increasing the quality of your system.

• Understand how patterns and reusable components enable the rapid development of reliable distributed systems
• Use the side-car, adapter, and ambassador patterns to split your application into a group of containers on a single machine
• Explore loosely coupled multi-node distributed patterns for replication, scaling, and communication between the components
• Learn distributed system patterns for large-scale batch data processing covering work-queues, event-based processing, and coordinated workflows

In many systems, scalability becomes the primary driver as the user base grows. Attractive features and high utility breed success, which brings more requests to handle and more data to manage. But organizations reach a tipping point when design decisions that made sense under light loads suddenly become technical debt. This practical book covers design approaches and technologies that make it possible to scale an application quickly and cost-effectively.

Author Ian Gorton takes software architects and developers through the foundational principles of distributed systems. You'll explore the essential ingredients of scalable solutions, including replication, state management, load balancing, and caching. Specific chapters focus on the implications of scalability for databases, microservices, and event-based streaming systems.

You will focus on:

• Foundations of scalable systems: Learn basic design principles of scalability, its costs, and architectural tradeoffs
• Designing scalable services: Dive into service design, caching, asynchronous messaging, serverless processing, and microservices
• Designing scalable data systems: Learn data system fundamentals, NoSQL databases, and eventual consistency versus strong consistency
• Designing scalable streaming systems: Explore stream processing systems and scalable event-driven processing

More and more enterprises today are dependent on cloud services from providers like AWS, Microsoft Azure, and GCP. They also use products, such as Kafka and Kubernetes, or databases, such as YugabyteDB, Cassandra, MongoDB, and Neo4j, that are distributed by nature. Because these distributed systems are inherently stateful systems, enterprise architects and developers need to be prepared for all the things that can and will go wrong when data is stored on multiple servers--from process crashes to network delays and unsynchronized clocks.

Patterns of Distributed Systems describes a set of patterns that have been observed in mainstream open-source distributed systems. Studying the common problems and the solutions that are embodied by the patterns in this guide will give you a better understanding of how these systems work, as well as a solid foundation in distributed system design principles.

Featuring real-world code examples from systems like Kafka and Kubernetes, these patterns and solutions will prepare you to confidently traverse open-source codebases and understand implementations you encounter "in the wild."

• Review the building blocks of consensus algorithms, like Paxos and Raft, for ensuring replica consistency in distributed systems
• Understand the use of logical timestamps in databases, a fundamental concept for data versioning
• Explore commonly used partitioning schemes, with an in-depth look at intricacies of two-phase-commit protocol
• Analyze mechanisms used in implementing cluster coordination tasks, such as group membership, failure detection, and enabling robust cluster coordination
• Learn techniques for establishing effective network communication between cluster nodes.

Along with enterprise architects and data architects, software developers working with cloud services such as Amazon S3, Amazon EKS, and Azure CosmosDB or GCP Cloud Spanner will find this set of patterns to be indispensable.

Reactive Design Patterns is a clearly written guide for building message-driven distributed systems that are resilient, responsive, and elastic. In this book you'll find patterns for messaging, flow control, resource management, and concurrency, along with practical issues like test-friendly designs. All patterns include concrete examples using Scala and Akka.